Overview of Integrated Assessment€¦ · – Simulation and optimization • Interpretation and...
Transcript of Overview of Integrated Assessment€¦ · – Simulation and optimization • Interpretation and...
Snowmass Workshop on CCI and IAJuly 30, 2009
Overview of Integrated AssessmentJohn P. Weyant
Stanford University
Outline
• What is Integrated Assessment?• Contributions of Integrated Assessment• Two Modes of Integrated Assessment • Examples of Integrated Assessment• Approaches to Uncertainty Analysis• Approaches to Setting Policy Objectives• Natural and Social Science Perspectives
ATMOSPHERIC COMPOSITION
HUMAN ACTIVITIES
CLIMATE & SEA LEVEL
ECOSYSTEMS
Atmospheric Chemistry
Ocean Carbon Cycle
Ocean* temperature* sea level
Climate
Terrestrial Carbon Cycle
Un-managed Eco-system
Energy System
Crops and Forestry
HydorlogyAgriculture, Livestock, &
Forestry
Other Human Systems
Coastal System
What is Integrated Assessment?(USGCRP/ Edmonds, Early 1990s)
What is Integrated Assessment?
Energy-economy
Early 1990s
Energy-economy
Late 1990s
Energy-economy
Present DayIn the Decade
Ahead
Ocean carbon cycle
Ocean carbon cycle
Ocean carbon cycle
Early 1980s
Atmos. Chem. Atmos. Chem. Atmos. Chem.
Terr. carbon cycle
Climate model Climate model Climate model
Ag-land-use
Sulfur aerosol Sulfur aerosol
Non-sulfur aerosol
Energy technology
Energy technology
Energy-economy
A major feature of future work will be an increased emphasis on
climate impacts on and adaptation by energy and other human and
natural systems.
Biodiversity
Timber
Manufacturing
Transport
Health
Energy Infrastructure
Energy Demand
Water Management
Energy-economy
Ocean carbon cycle
Atmos. Chem.
Terr. carbon cycle
Ag-land-use
Unmanaged Ecosystems
Climate model
Sulfur aerosol
Non-sulfur aerosol
Hydrology
Energy technology
Fisheries
Fully closed systems
Energy impacts
Urban air quality
Ocean acidification
Coastal zones
Sea level and Ice
Evolution of IA (Edmonds)
Contributions of Integrated Assessment
– Internal Consistency Checks – Insights Like The Four Flexibilities– Rough Numbers To Guide Policy Development– Research Prioritization– Put Probabilities on Future Climate Outcomes
Two Modes of Integrated Assessment
• Policy-Oriented Simulations – Focused on Simulating Effects of Policies– Usually Much More Detailed Impacts– Can be Run Backwards - Tolerable Windows Approach
• Cost-Benefit Modeling– Focused on Finding “Optimal” Level of Emissions– Usually Include Impacts at the Aggregate Level– Can Be Run In Cost Effectiveness Mode
Example #1: IPCC “Meta Simulation”
Example #1: IPCC “Meta Simulation”Flaming Embers
Example #1: IPCC “Meta Simulation”
Cost/Benefit Modeling Approach:Balancing the Costs of Controlling Carbon Emissions Against the Costs of the Climate Impacts They Cause
Value/Cost of
Emissions Reductions
Carbon Emissions
Marginal Cost of Climate Impacts
Marginal Cost of Emissions Control
Example# 2: C/B Results From Nordhaus “A Question of Balance” Book 7/2008
Example# 2: C/B Results From Nordhaus “A Question of Balance” Book 7/2008
Four Kinds of Mitigation Policy Flexibilities
1. Where Flexibility2. When Flexibility3. How Flexibility4. What Flexibility
Example #3: Merge-Flexibility Analysis
Example #4: PNNL MiniCAM Land/Biofuels
Example # 4: PNNL MiniCAM Land/Biofuels
SCIENCE VOL 324 29 MAY 2009
Example #5 - MIT IGSM
Example #5 - MIT IGSM
Approaches to Uncertainty Analysis• Sensitivity Analysis• Stochastic Simulation• Decision Making Under Uncertainty
– Sequential DMUU– Decision Analysis– Stochastic Control– Robust Planning
• Formulation– Who knows what, when, and what can they do with that info.– Information structure, dynamics, and stochastics
• Probability Assessment– Statistical– Subjective– Combinations
• Computation– Software and hardware– Simulation and optimization
• Interpretation and communication of results– Many dimensions for inputs, policies and outputs– Need for focusing on needs of decision makers grows exponentially
• These elements need to be designed and implemented together
Four Interdependent Elements of Any Uncertainty Analysis
IPCC AR4 PdFs Given Emissions
MIT Joint Emissions & Climate PdFs
Decision Analysis ApproachHedging Against Bad Climate Outcomes
0
5
10
15
20
25
2000 2010 2020 2030 2040 2050 2060 2070 2080 2090 2100Year
Glob
al C
arbo
n Em
issi
ons
(GtC
)
Reference90% Probability Scenario10% Probability ScenarioHedge/90% ScenarioHedge/10% Scenario
Approaches to Setting Climate Policy Objectives• Cost Effective Analysis- Careful Choice of Target(s) and
Then Minimize Costs to Achieve It• Formal Cost/Benefit Analysis• Sequential Decision Making Under Uncertainty
• Decision Theory Based• Hard to Implement• Get Value of Information About Key Uncertainties
• Less Comprehensive Approaches• Tolerable Windows• Robust Planning Methods• Tolerable Windows With Cost Effectiveness Iteration• Evolutionary Theory Based Approaches-Simple Rules
Some Things We Find in Economics,But Not in Natural Sciences
• Preferences (possibly changing over time)• Expectations (certainly changing over time)• The ability to make contingent decisions• These characteristics may lead to differences in:
– Framing questions– Modeling systems– Integrating models– Assessing models
Two Different Objectives:Forecast Accuracy Versus Policy Insights
• “Science community” has focused more on forecast accuracy and uncertainty measurement.
• “IA community” has focused more on policy insights, and uncertainty characterization.
• These different perspectives have lead to very different ways of operating.
• The RCP approach may be a model for how to bridge the gap in a useful way.
Possible To IAM Do List• Appreciate/use the insights we are already getting from IAMs.
– To guide science priorities.– In a way that guides policy development.
• Apply appropriate science community validation & uncertainty measurement techniques to science modules of IAMs.
• Develop better ways to project and characterize uncertainty regarding socio-economic drivers and structural elements of IAMs.
• Develop a more integrated argument for employing a sequential decision making under uncertainty framework for deciding what to do about climate change.
• Develop strategies for integrating IAV concerns/ interests into the process.– Gridded socio-economic data from IAMs? – Further vulnerability analyses?– Develop strategic plan for where to focus first, second, etc.?– Uncertainty and validation methods.– Regional IAMs
Thank You!
Evolution of IA Modeling
Energy-economy
Early 1990s
Energy-economy
Late 1990s
Energy-economy
Present Day
Energy-economy
Future
Ocean carbon cycle
Ocean carbon cycle
Ocean carbon cycle
Ocean carbon cycle
Atmos. Chem.
Terr. carbon cycle
Ag-land-use
Ecosystem impacts
Energy-economy
Early 1980s
Atmos. Chem.
Atmos. Chem.
Atmos. Chem.
Terr. carbon cycle
Climate model
Climate model
Climate model
Climate model
Ag-land-use
Sulfur aerosol
Sulfur aerosol
Sulfur aerosol
Non-sulfur aerosol
Non-sulfur aerosol
Hydrology
Energy technology
Energy technology
Energy technology
Closed system
Source: J. Edmonds - JGCRI
Some Areas Where Some Integration Has Proven Useful
• Biological Sinks• CO2 Fertilization• Sulfate Aerosols• Biofuels Assessments• Health Impact Assessments
The VALUE OF DEVELOPINGNEW ENERGY TECHNOLOGY
(Present Discounted Costs to Stabilize the Atmosphere)
Minimum Cost Based on Perfect Where & When
Flexibility Assumption. Actual Cost
Could be An Order of
Magnitude Larger.
BAU(1990)BAU(Tech+)
advancedtechnology
550
650
750
$1
$10
$100
$1,000
$10,000
$100,000
Present Discounted C
ost, Billions of 1990 U
S $
Technology Assumption
Steady-State CO2
Concentration (ppmv)
Battelle Pacific Northwest Laboratories
3. How Flexibility
What is Integrated Assessmentof Climate Change Policy?
• Many definitions of IA for many purposes• Here we call integrated assessment of climate
change policy any attempt to bring together the costs and benefits of climate change policies in a systematic manner
Background Questions• Why assess?
– Need insights and numbers for policy development• Why model?
– Consistency– Insights– Learning– Rough numbers +sensitivities
• What principles to use?– Disciplinary differences– What is empirical evidence?
• How should models be evaluated?– Backcasting– Model assessment
• Who decides these things? – Disciplines, national academies, lawyers, us
End to End Approachto Integrated Assessment
ATMOSPHERIC COMPOSITION
EMISSIONS CLIMATE & SEA LEVEL
Atmospheric Chemistry
Ocean Carbon Cycle
Ocean* temperature* sea level
ClimateEnergy System
Agriculture
Other Emissions
IMPACTSEnergy System
Agriculture, Livestock, &
Forestry
Health & Other
Impacts
Coastal System
Types of Integrated Assessment Models
DeterministicPolicy Optimization Models
DeterministicPolicy Evaluation Models
Decision Making Under Uncertainty Models
StochasticPolicy Optimization Models
Deterministic Models
Stochastic Policy Evaluation Models
Uses Of Integrated Assessment Models
DeterministicPolicy Optimization Models
DeterministicPolicy Evaluation Models
Decision Making Under Uncertainty Models
StochasticPolicy Optimization Models
Stochastic Policy Evaluation Models
Deterministic Models
- Compute Optimal Carbon Taxes, Control Rates, etc.
-Calculate Costs of Meeting Emission/Concentration/Climate/Impact Targets
- Insure Consistency in Assumptions- Assess Interactions and Feedbacks- Identify Critical Gaps in Research
-Assess Optimal Policies Under Uncertainty
-Compute Value ofInformation/Research
- Compute Probabilities ofCost/Benefits of Climate Policies
- Compute Probabilities of Meeting Targets
Components of Mitigation Costs
• Direct resource costs• Indirect opportunity costs
– Less of one commodity, but perhaps more of another– Can include shifts in industry structure– Can include trade impacts
• Economic growth impacts– Tied into capital accumulation– Also depends heavily on technological change
• Dis-eqilibrium impacts
! Agriculture! Forestry! Sea Level Rise! Water Supply! Energy Consumption! Fisheries! Extreme
Events/Insurance
! Unmanaged Eco-Systems– Terrestrial– Marine
! Human Health*! Bio-Diversity*! Wildlife! Recreation*! Amenities
MARKET NON-MARKET
*Some Market Components
Areas Where Climate Change Impacts Are Anticipated
And Then We Have The Bottom-Up Engineering Models:
IPCC AR4 Global Mitigation Cost Estimates
A Range of Approaches to Projecting Mitigation Costs
Frontiers in Integrated Assessment
• Coping with complexity• Incorporating uncertainty• Embracing technological change• Integrating the sciences• Synthesizing the impacts• Promoting development
I. Coping With Complexity
• Need to Maintain Problem Focus• Proliferation of Data, Modules, Interactions• Need Strategic Approach to
Formulation/Implementation• Lessons From Complexity Theory?• Operationalize Multi-Level Cyclical Scaling?
Costs of Stabilizing Concentrations at 550 ppmv -- discounted to 1990 at 5 %
-5
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5
10
15
20
WGI-no t
rade
WGI-trad
e
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rade
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rade
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rade
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rade
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WRE-no tra
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WRE-trade
Trill
ions
of 1
990
dolla
rs
non-Annex 1EEFSUOECD
CETA
FUND
MERGEMiniCAM
CPMRIVM SGM
2. Where and When Flexibility
Year 2010 Carbon Tax Comparision for the United States
0
50
100
150
200
250
300
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400
450
Oxf
ord
ABA
RE-G
TEM
NEM
S
MER
GE3
MS-
MRT
MIT
-EPP
A
SGM
CETA
MA
RKA
L-M
acro
AIM
RICE
Wor
ldSc
an
G-C
ubed
FUN
D
Model
No Trading Annex I Trading Global Trading
Car
bon
Tax
(199
0$s/M
etric
Ton
)
The Cost of Kyoto1. Where Flexibility
RCP Candidates:Published Scenarios With All Gases
Carbon Permit Price (2000 $USD / tC) in CO2-Only (solid) and Multigas (dashed) Scenarios
0
1000
2000
3000
4000
5000
2000 2025 2050 2075 2100
AIMAMIGACOMBATEDGEEPPAFUNDGEMINI-E3GRAPEGTEMIMAGEIPACMERGEMESSAGEMiniCAMSGMWIAGEM
(4.5 W/m2 Cap on Radiative Forcing)
4. What Flexibility
II. Incorporating UncertaintyInformation, Foresight & Uncertainty:Three Alternative Sets of Assumptions
Invest StartOperation
StopOperation
State of Energy System
Time
Plan & Build Operate
t1 t2t0
(1) Static, Myopic, or Recursive Dynamic(2) Perfect Foresight (Rationale Expectations)(3) Decision Making Under Uncertainty
Interplay BetweenR&D and Investment Decisions
R&DDecision
C0
InvestmentDecision
C1C1 C2
!Cost Cost
Time
III. Embracing Technological ChangeLimitations and Possible Extensions to
Current Methods for Modeling ITSCurrent approaches omit important dynamics of technologicalchange. A broader framework for analyzing ITC is needed.
Private R&DInvestment
HeterogeneousInnovators
(“Returns to R&D”)
Uncertainty inR&D Returns:
Discontinuous Diffusion
UncertainTax Policy
Path-dependenceand inertia
Innovation &Knowledge
Accumulation
IntersectoralSpillovers
Technological Change:Diffusion and
Market Penetration
Learning-by-Doing
Public R&DSpillovers
MajorInnovation
IntrasectoralSpillovers
OUTSIDE INFLUENCESINDUCED CHANGE
Total R&D Investment
TechnologicalChange
Returnsto R&D
Tax Policy Spillovers
What is Integrated Assessment?
Observations Regarding Current Approaches to Modeling ITC
• Current approaches to ITC provide a good foundation:– spillovers– innovation incentives and knowledge capital– heterogeneous firms and technologies
• Current approaches suggest weak or ambiguous effect of ITC, butunderestimate importance:
– Focus only on R&D-based technological change» learning-by-doing» diffusion or imitation by existing technology
– Assume continuous, known returns to R&D function (no surprises or discontinuities)» No provision for major innovations» Model only one dimension of technological change (cost)
– Neglect path-dependence and inertia in changing technology dynamics
• Modeling challenge will be to incorporate enough complexity torealistically capture technology dynamics in a meaningful way.
• Policy challenge will be to use insights from models, but qualify findingswith a more complete understanding of technological evolution.
ATMOSPHERIC COMPOSITION
HUMAN ACTIVITIES
CLIMATE & SEA LEVEL
ECOSYSTEMS
Atmospheric Chemistry
Ocean Carbon Cycle
Ocean* temperature* sea level
Climate
Terrestrial Carbon Cycle
Un-managed Eco-system
Energy System
Crops and Forestry
HydorlogyAgriculture, Livestock, &
Forestry
Other Human Systems
Coastal System
IV. Integrating The SciencesAre We Integrated or…
…Still End-to-End ?ATMOSPHERIC COMPOSITION
EMISSIONS CLIMATE & SEA LEVEL
Atmospheric Chemistry
Ocean Carbon Cycle
Ocean* temperature* sea level
ClimateEnergy System
Agriculture
Other Emissions
IMPACTSEnergy System
Agriculture, Livestock, &
Forestry
Health & Other
Impacts
Coastal System
Do we need Integrated Earth Systems Models?
V. Synthesizing The Impacts:Where We Are In Impacts/Adaptation Analyses
• Reasonable economics estimates in a few sectors– Agriculture– Forestry– Sea level rise
• Preliminary physical impacts representations in others– Health– Wildlife– Water supply
• First order causal mechanisms in others– Unmanaged eco-systems– Biodiversity– Extreme events – both changes in variability and abrupt changes
• How to weigh what we know and don’t know and what we can measure or not measure and what we can value and not value is a big challenge
Key Challenges Facedin Projecting Impacts
• Projecting Regional Climate– Temperature– Precipitation– Variability
• Projecting Baseline Conditions• Transient Versus Equilibrium Impacts• Factoring In Adaptation• Valuing Non-Market Impacts
Emissions
AlternativeDevelopment
Pathways
DevelopmentEquity
Sustainability
Environmental &Socio-Economic
Impacts
Climate Policy
Sustainable Development
PolicyAda
ptat
ion,
Vu
lner
abili
ty
Miti
gatio
n
Finance, Technology, Livelihoods
Vis
ion,
Life
styl
es
Plate 1: Efficiency
Plate 2: Equity
Plate 3: Sustainability
Costsco-benefits
VI. Promoting Development
Whither the Poor and Defenseless?A Revealed Preference Study
of Climate Change Policy AnalysesClass ofWorld Citizen
Typical OECD (AEA Member?)Analysis
ROW Analysis
2 Billion PeopleWithout Markets
What 2 BillionPeople?
High Priority:Reduce TheirVulnerability
2 Billion In or NearPoverty with FragileMarkets
They Don’t Countfor Much!
High Priority:Reduce TheirVulnerability
2 Billion PotentialDecaf LattéDrinkers
Half Are Stuck InTransition, But theRest We Can Help
They Can TakeCare ofThemselves
Potential Areas of Model Refinement (I)1. Technology/Technology Change
– Invention– Innovation– Diffusion
2. Spatial/Temporal Disaggregation3. Uncertainty
– In the World, aka Scenario Uncertainty– How it Impacts Behavior of Modeled Agents– Related to Degree of Foresight Assumed
4. Data– Technology, Energy End Uses, Resources– Institutions– Economic Output, I/O, Fuel Markets, Trade
Potential Areas of Model Refinement (II)5. Representation of Market Imperfections6. Representation of “Non-Rational” Behavior7. Ability to Analyze “Plausible” Policies
• Standards• Sectoral Caps• Remedies for Market Imperfections
8. Macro/Microeconomic Integration9. Public Finance/Financial Market Integration10. Marrying Conceptual Structures With Data
Integrated Assessmentof Integrated Assessments?
– Peer Reviewed Proposals– Peer Reviewed Literature– Forum Analysis– Model Assessment Projects– PCMDI-Like Institution– Other
Basic Strategies for Developing Models
• Identify All Potential Questions First, Then Design the Model to Help Address Them
• Develop a Flexible Modeling Architecture That Can Be Easily Adapted to New Problems
• Do Both!
Model Development/Assessment Issues:Common Pitfalls in Policy Modeling
• Lack of Focus– Pick a basic model structure without a set of applications
firmly in mind– Not modifying model in response to new problems
• Mistaking the Model for Reality– If its not in the model it probably doesn’t exist– Test alternative assumptions only against the model– Methodological limitations imply real world restrictions
• Poor Communication of Results– Overstating strength of results– Omitting key relevant assumptions/qualifications
Table 1: Technology Assumptions Year 2100
Technology units 1990 Base
Mini-CAM B2
Mini-CAM B2
AT US Automobiles mpg 18 60 100
Land-based Solar Electricity 1990 c/kWh 61 5.0 5.0 Nuclear Power 1990 c/kWh 5.8 5.7 5.7
Biomass Energy 1990$/gj $7.70 $6.30 $4.00 Hydrogen Production (CH4 feedstock) 1990$/gj $6.00 $6.00 $4.00
Fuel Cell mpg (equiv) 43 60 98 Fossil Fuel Power Plant Efficiency (Coal/Gas) % 33 42/52 60/70
Capture Efficiency % 90 90 90 Carbon Capture Power Penalty (Coal) % 25 15 5 Carbon Capture Power Penalty (Gas) % 13 10 3 Carbon Capture Capital Cost (Coal) % 88 63 5 Carbon Capture Capital Cost (Gas) % 89 72 3
Geologic Disposal (CO2) $/tC 37.0 37.0 23.0
Technology is King
Cost/Benefit Modeling Approach:Balancing the Costs of Controlling Carbon Emissions Against the Costs of the Climate impacts They Cause
Value/Cost of
Emissions Reductions
Carbon Emissions
Marginal Cost of Climate Impacts
Marginal Cost of Emissions Control
Marginal Cost of Carbon Emission Reductions in the United States in 2010
0
50
100
150
200
250
300
350
400
450
0 5 10 15 20 25 30 35 40 45 50
% Reduction in Carbon Emissions wrt Reference
Car
bo
n T
ax(1
990
$US
/met
ric
ton
)
AIM
CETA
MIT-EPPA
G-Cubed
ABARE-GTEM
MERGE3
MS-MRT
Oxford
RICE
SGM
WorldScan
NEMS
The Substitution in the Models
0.00
200.00
400.00
600.00
800.00
1000.00
1200.00
1400.00
1600.00
1800.00
Ex
ajo
ule
s
AIM
DN
E2100
GR
AP
E
MA
RIA
MIn
iCA
M
EP
PA
IIA
SA
IMA
GE
Model
World Primary Energy in 550 ppm Case in 2100
OtherBiomassWindSolarNuclearHydroCoalGasOil
The Energy Resource Mix